Research Specialist in Data Science and Marine Socio-ecological Systems

KAUST

Thuwal

On-site

SAR 180,000 - 240,000

Full time

14 days+
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Job summary

King Abdullah University of Science and Technology in Thuwal, Saudi Arabia, invites applications for a Research Specialist in the Integrated Reef Fisheries Lab. You will support data-driven research on coral reef fisheries by managing large datasets, building pipelines, performing analyses, and helping design robust workflows in collaboration with Professor Jessica Zamborain Mason's team.

This role emphasizes reproducible research, code documentation, manuscript support, and mentorship of new

Qualifications

  • Bachelor’s or Master’s degree in data science, statistics, computer science, environmental science, or a related quantitative field.
  • Strong proficiency in R for data manipulation, analysis, and visualization.
  • Familiarity with Git and GitHub for version control and collaborative coding.
  • Excellent communication, writing, and organizational skills.
  • Proven ability to work with large and complex datasets.
  • Experience contributing to peer‑reviewed publications.
  • Demonstrated ability to work independently and collaboratively in multidisciplinary research environments.

Responsibilities

  • Develop, maintain, and optimize data pipelines for collecting, cleaning, harmonizing and transforming large and complex datasets including a range of environmental, ecological, social and economic variables.
  • Conduct statistical and geospatial analyses, data visualization, and mechanistic modeling as required by project goals.
  • Ensure data integrity, reproducibility, and documentation throughout the research lifecycle.
  • Collaborate with the PI to interpret and summarize analytical results.
  • Conduct literature reviews and synthesize findings relevant to ongoing research topics.
  • Assist in preparing manuscripts, reports, presentations, and grant proposals.
  • Contribute to writing methods sections and developing reproducible analysis scripts.
  • Manage code repositories and collaborative workflows using GitHub/GitLab.
  • Maintain documentation of code, workflows, and data sources.
  • Contribute to the development of automated pipelines and reproducible research frameworks.
  • Support the PI in coordinating research activities, meetings, and lab schedules.
  • Assist with data sharing, compliance, and ethics documentation.
  • Help onboard and mentor new lab members in data practices and computational tools.

Skills

R proficiency
Git/GitHub
Communication
Data management
Publications experience
Collaboration

Education

Bachelor’s or Master’s in Data Science/Statistics/CS/Environmental Science

Tools

Git
GitHub

Job description

King Abdullah University of Science and Technology: Postdoc Positions: Biological and Environmental Science and Engineering Division (postdoc)

We are seeking a highly motivated and quantitatively skilled Research Specialist with a strong background in data science, statistics, and programming to support ongoing and new research projects in the Integrated Reef Fisheries Lab at KAUST.

The Integrated Reef Fisheries Lab is dedicated to enhancing the sustainability of coral reef fisheries and aquatic food systems both in the Kingdom and around the world. Through collaborative, data-driven research, we integrate ecological, social, and economic data to develop innovative tools and strategies that support resilient fisheries and communities. Working closely with local stakeholders and global partners, our interdisciplinary team strives to create practical solutions that ensure the long‑term health and productivity of reef ecosystems worldwide—especially in the face of climate change.

The research specialist will work closely with Professor Jessica Zamborain Mason and her team to conduct data-driven analyses, manage large and complex databases, support research design, assist in manuscript preparation, and help maintain smooth lab operations.

Are you passionate about using data science to tackle real‑world environmental challenges? Be part of a team that turns data into solutions—protecting ecosystems and empowering communities worldwide.

1. Data Management & Analysis
  • Develop, maintain, and optimize data pipelines for collecting, cleaning, harmonizing and transforming large and complex datasets including a range of environmental, ecological, social and economic variables.
  • Conduct statistical and geospatial analyses, data visualization, and mechanistic modeling as required by project goals.
  • Ensure data integrity, reproducibility, and documentation throughout the research lifecycle.
  • Collaborate with the PI to interpret and summarize analytical results.
2. Research & Writing Support
  • Conduct literature reviews and synthesize findings relevant to ongoing research topics.
  • Assist in preparing manuscripts, reports, presentations, and grant proposals.
  • Contribute to writing methods sections and developing reproducible analysis scripts.
3. Technical Infrastructure
  • Manage code repositories and collaborative workflows using GitHub/GitLab.
  • Maintain documentation of code, workflows, and data sources.
  • Contribute to the development of automated pipelines and reproducible research frameworks.
  • Support the PI in coordinating research activities, meetings, and lab schedules.
  • Assist with data sharing, compliance, and ethics documentation.
  • Help onboard and mentor new lab members in data practices and computational tools.
Qualifications
  • Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Environmental Science, or a related quantitative field.
  • Strong proficiency in R for data manipulation, analysis, and visualization.
  • Familiarity with Git and GitHub for version control and collaborative coding.
  • Excellent communication, writing, and organizational skills.
  • Proven ability to work with large and complex datasets.
  • Experience contributing to peer‑reviewed publications.
  • Demonstrated ability to work independently and collaboratively in multidisciplinary research environments.
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